Sweetgum Genetic Study

General info

I created this website to track the progress with the sweetgum genetic study.

There are 7 parts:

1. Libraries, dataset loading, and data wrangling.
2. SAS code.
3. Survival rate plots.
4. Groundline diameter (GLD) plots and stats.
5. Tree height plots and stats.
6. DBH plots and stats.
7. Live crown height plots and stats.

Data Wrangling

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.0
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(ggpubr)
library(plotly)

## 
## Attaching package: 'plotly'
## 
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## 
## The following object is masked from 'package:stats':
## 
##     filter
## 
## The following object is masked from 'package:graphics':
## 
##     layout

sweetgum_genetic1 <- read.csv("https://raw.githubusercontent.com/azd169/R-datasets/main/sweetgum_genetic.csv",
                              header = T)

sweetgum_genetic <- sweetgum_genetic1 %>%
  dplyr::mutate_if(is.integer, as.numeric) %>%
  dplyr::mutate_if(is.character, as.factor) %>%
  dplyr::mutate(Location = recode_factor(Location,
                                         "LA_Tech" = "LA Tech",
                                         "Hill_Farm" = "Hill Farm")) %>%
  dplyr::mutate(Year = recode_factor(Year,
                                     "Year_0" = "Initial",
                                     "Year_1" = "First",
                                     "Year_2" = "Second",
                                     "Year_3" = "Third",
                                     "Year_4" = "Fourth",
                                     "Year_5" = "Fifth",
                                     "Year_6" = "Sixth",
                                     "Year_7" = "Seventh")) %>%
  dplyr::mutate_if(is.numeric, round, 2)

# Robert's dataset for his thesis

hane_gld <- sweetgum_genetic %>%
  subset(Year %in% c("Initial", "First", "Second")) %>% 
  subset(Border %in% c("0")) %>% #
  dplyr::group_by(Year, Location, Family, Block) %>%
  dplyr::summarize(GLD = mean(GLD, na.rm = T)) %>%
  dplyr::mutate(GLB = paste(Family, Location, Block, sep = "_")) 

## `summarise()` has grouped output by 'Year', 'Location', 'Family'. You can
## override using the `.groups` argument.

hane_dbh <- sweetgum_genetic %>%
  subset(Year %in% c("Third", "Fourth", "Fifth", "Sixth", "Seventh")) %>% 
  subset(Border %in% c("0")) %>% #
  dplyr::group_by(Year, Location, Family, Block) %>%
  dplyr::summarize(DBH = mean(DBH, na.rm = T)) %>%
  dplyr::mutate(GLB = paste(Family, Location, Block, sep = "_"))

## `summarise()` has grouped output by 'Year', 'Location', 'Family'. You can
## override using the `.groups` argument.

hane_crown <- sweetgum_genetic %>%
  subset(Year %in% c("Fifth", "Sixth", "Seventh")) %>% 
  subset(Border %in% c("0")) %>% #
  dplyr::group_by(Year, Location, Family, Block) %>%
  dplyr::summarize(Crown = mean(Crown_height, na.rm = T)) %>%
  dplyr::mutate(GLB = paste(Family, Location, Block, sep = "_"))

## `summarise()` has grouped output by 'Year', 'Location', 'Family'. You can
## override using the `.groups` argument.

hane_ht <- sweetgum_genetic %>%
  dplyr::select(-c(GLD, DBH, Crown_height, Survival)) %>%
  subset(Border %in% c("0")) %>%
  group_by(Year, Location, Family, Block) %>%
  summarize(Height = mean(Height, na.rm = T)) %>%
  mutate(GLB = paste(Family, Location, Block, sep = "_")) %>%
  mutate(Year = as.factor(Year),
         Location = as.factor(Location),
         Family = as.factor(Family),
         GLB = as.factor(GLB))

## `summarise()` has grouped output by 'Year', 'Location', 'Family'. You can
## override using the `.groups` argument.

hane_survival_year <- sweetgum_genetic %>%
  subset(Year %in% c("Initial", "First", "Second")) %>% 
  subset(Border %in% c("0")) %>%
  group_by(Year, Survival) %>%
  summarise(n = n()) %>%
  mutate(Rate = (n / sum(n))*100) %>%
  dplyr::mutate_if(is.numeric, round, 2)

## `summarise()` has grouped output by 'Year'. You can override using the
## `.groups` argument.
## `mutate_if()` ignored the following grouping variables:

hane_survival_year_location <- sweetgum_genetic %>%
  subset(Year %in% c("Initial", "First", "Second")) %>% 
  subset(Border %in% c("0")) %>%
  group_by(Year, Location, Survival) %>%
  summarise(n = n()) %>%
  mutate(Rate = (n / sum(n))*100) %>%
  dplyr::mutate_if(is.numeric, round, 2)

## `summarise()` has grouped output by 'Year', 'Location'. You can override using
## the `.groups` argument.
## `mutate_if()` ignored the following grouping variables:

hane_survival_year_family <- sweetgum_genetic %>%
  subset(Year %in% c("Initial", "First", "Second")) %>% 
  subset(Border %in% c("0")) %>%  
  group_by(Year, Family, Survival) %>%
  summarise(n = n()) %>%
  mutate(Rate = (n / sum(n))*100) %>%
  dplyr::mutate_if(is.numeric, round, 2)

## `summarise()` has grouped output by 'Year', 'Family'. You can override using
## the `.groups` argument.
## `mutate_if()` ignored the following grouping variables:

hane_survival_year_location_family <- sweetgum_genetic %>%
  subset(Year %in% c("Initial", "First", "Second")) %>% 
  subset(Border %in% c("0")) %>%  
  group_by(Year, Location, Family, Survival) %>%
  summarise(n = n()) %>%
  mutate(Rate = (n / sum(n))*100) %>%
  dplyr::mutate_if(is.numeric, round, 2)

## `summarise()` has grouped output by 'Year', 'Location', 'Family'. You can
## override using the `.groups` argument.
## `mutate_if()` ignored the following grouping variables:

SAS Code

Procedure:

External trees were removed from the analysis and all the Variables were averaged at plot level. A unique ID was created combining Genotype, Location, and Block (GLD in the SAS code)

Datasets used:

1. WORK.DBH for DBH
2. WORK.GLD for GLD
3. WORK.HEIGHT for tree height
4. WORK.CROWN for crown height

Here are the SAS models:

1. GLD

PROC GLIMMIX DATA = GLD H PLOTS = ALL; CLASS Year Location Block Family GLB; MODEL GLD = Year|Location|Family / SOLUTION DDFM = KR; RANDOM intercept / SOLUTION SUBJECT = GLB TYPE = AR(1) CL; LSMEANS Location Family Year * Location Year * Family/ ADJUST = TUKEY LINES; ODS GRAPHICS OFF; RUN;

2. Height

PROC GLIMMIX DATA = HEIGHT H PLOTS = ALL; CLASS Year Location Block Family GLB; MODEL Height = Year|Location|Family / SOLUTION DDFM = KR; RANDOM intercept / SOLUTION SUBJECT = GLB TYPE = AR(1) CL; LSMEANS Family/ ADJUST = TUKEY LINES; SLICE Year * Location / SLICEBY = Year ADJUST = TUKEY LINES DIFF; SLICE Year * Family / SLICEBY = Year ADJUST = TUKEY LINES DIFF; ODS GRAPHICS OFF; RUN;

3. DBH

PROC GLIMMIX DATA = DBH H PLOTS = ALL; CLASS Year Location Block Family GLB; MODEL DBH = Year|Location|Family / SOLUTION DDFM = KR; RANDOM intercept / SOLUTION SUBJECT = GLB TYPE = AR(1) CL; LSMEANS Family/ ADJUST = TUKEY LINES; SLICE Year * Location / SLICEBY = Year ADJUST = TUKEY LINES DIFF; SLICE Year * Family / SLICEBY = Year ADJUST = TUKEY LINES DIFF; ODS GRAPHICS OFF; RUN;

4. Crown Height

PROC GLIMMIX DATA = CROWN H PLOTS = ALL; CLASS Year Location Block Family GLB; MODEL CROWN = Year|Location|Family / SOLUTION DDFM = KR; RANDOM intercept / SOLUTION SUBJECT = GLB TYPE = AR(1) CL; LSMEANS Family/ ADJUST = TUKEY LINES; SLICE Year * Location / SLICEBY = Year ADJUST = TUKEY LINES DIFF; SLICE Year * Family / SLICEBY = Year ADJUST = TUKEY LINES DIFF; ODS GRAPHICS OFF; RUN;

Survival rates

Sur1 <- ggplot(hane_survival_year,
               aes(x = Survival, y = Rate, fill = Survival)) +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 100), breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("green4", "red3"), 0.5)) +
  labs(title = "Survival Rate by Growing Season") +
  xlab("") +
  ylab("Survival rate (%)") +
  facet_wrap( ~ Year) +
  guides(fill = guide_legend()) +
  theme_classic()

plotly::ggplotly(Sur1)

Sur2 <- ggplot(hane_survival_year_family,
               aes(x = Family, y = Rate, fill = Survival)) +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 100), breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("green4", "red3"), 0.5)) +
  labs(title = "Survival Rate by Growing Season and Family") +
  xlab("") +
  ylab("Survival rate (%)") +
  facet_wrap( ~ Year) +
  guides(fill = guide_legend()) +
  theme_classic()

plotly::ggplotly(Sur2)

Sur3 <- ggplot(hane_survival_year_location,
               aes(x = Location, y = Rate, fill = Survival)) +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 100), breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("green4", "red3"), 0.5)) +
  labs(title = "Survival Rate by Growing Season and Location") +
  xlab("") +
  ylab("Survival rate (%)") +
  facet_wrap( ~ Year) +
  guides(fill = guide_legend()) +
  theme_classic()

plotly::ggplotly(Sur3)

Sur4 <- ggplot(hane_survival_year_location_family,
               aes(x = Family, y = Rate, fill = Survival)) +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 100), breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("green4", "red3"), 0.5)) +
  labs(title = "Survival Rate by Growing Season, Location, and Family") +
  xlab("") +
  ylab("Survival rate (%)") +
  facet_wrap( ~ Year + Location, ncol = 2) +
  theme_classic()

plotly::ggplotly(Sur4)

GLD

Fig1 <- ggplot(hane_gld,
                 aes(x = Family, y = GLD, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 60), breaks = c(0, 10, 20, 30, 40, 50, 60), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "GLD: Family Effect") +
  xlab("Family") +
  ylab("GLD (mm)") +
  annotate("text",
           x = c(1, 2, 3, 4, 5, 6),
           y = c(50),
           label = c("b", "ab", "a", "a", "ab", "ab")) +
  theme_classic()

plotly::ggplotly(Fig1)

Fig2 <- ggplot(hane_gld,
               aes(x = Year, y = GLD, fill = Location)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 70), breaks = c(0, 10, 20, 30, 40, 50, 60, 70), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#000000", "#999999"), 0.5)) +
  labs(title = "GLD: Year * Location") +
  xlab("Growing Season") +
  ylab("GLD (mm)") +
  annotate("text",
           x = c(1.78, 2.22, 2.78, 3.22),
           y = c(20, 20, 55, 50),
           label = c("b", "a", "a", "b")) +
  theme_classic()

plotly::ggplotly(Fig2)

Fig3 <- ggplot(hane_gld,
               aes(x = Year, y = GLD, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 80), breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                               "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "GLD: Year * Family") +
  xlab("Growing Season") +
  ylab("GLD (mm)") +
  annotate("text",
           x = c(2.62, 2.78, 2.93, 3.08, 3.22, 3.38),
           y = c(45, 50, 55, 60, 55, 55),
           label = c("b", "b", "a", "a", "a", "a")) +
  theme_classic()

plotly::ggplotly(Fig3)

Height

Fig4 <- ggplot(hane_ht,
               aes(x = Family, y = Height, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 12), breaks = c(0, 2, 4, 6, 8, 10, 12), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "Height: Year * Location") +
  xlab("Family") +
  ylab("Height (m)") +
  annotate("text",
           x = c(1, 2, 3, 4, 5, 6),
           y = c(10),
           label = c("d", "cd", "a", "a", "bc", "ab")) +
  theme_classic()

plotly::ggplotly(Fig4)

Fig5 <- ggplot(hane_ht,
                  aes(x = Year, y = Height, fill = Location)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 12), breaks = c(0, 2, 4, 6, 8, 10, 12), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#000000", "#999999"), 0.5)) +
  labs(title = "Height: Year * Location" ) +
  xlab("Growing Season") +
  ylab("Height (m)") +
  annotate("text",
           x = c(3.78, 4.22, 4.78, 5.22, 5.78, 6.22, 6.78, 7.22),
           y = c(5, 4, 7, 5.5, 8.5, 7.5, 11, 7.5),
           label = c("a", "b", "a", "b", "a", "b", "a", "b")) +
  theme_classic()

plotly::ggplotly(Fig5)

Fig6 <- ggplot(hane_ht,
               aes(x = Year, y = Height, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 12), breaks = c(0, 2, 4, 6, 8, 10, 12), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "Height: Year * Family") +
  xlab("Growing Season") +
  ylab("Height (m)") +
  annotate("text",
           x = c(2.63, 2.77, 2.92, 3.06, 3.22, 3.38,
                 3.63, 3.77, 3.92, 4.06, 4.22, 4.38,
                 4.63, 4.77, 4.92, 5.06, 5.22, 5.38,
                 5.63, 5.77, 5.92, 6.06, 6.22, 6.38,
                 6.63, 6.77, 6.92, 7.06, 7.22, 7.38,
                 7.63, 7.77, 7.92, 8.06, 8.22, 8.38
                 ),
           y = c(2.2, 2.5, 3, 3.3, 2.7, 2.9,
                 3.1, 3.3, 4.3, 4.5, 3.7, 3.9,
                 5, 5.5, 6.5, 6.8, 5.9, 6.2,
                 6.5, 7, 8.1, 8.4, 7.4, 7.8,
                 7.7, 8.5, 10.4, 10.4, 9.8, 10.2,
                 9.3, 9.2, 10.5, 10.4, 10, 10.3
                 ),
           label = c("c", "bc", "a", "a", "abc", "ab",
                     "c", "bc", "a", "a", "bc", "ab",
                     "d", "cd", "ab", "a", "bc", "ab",
                     "c", "bc", "a", "a", "b", "a",
                     "c", "c", "a", "a", "b", "ab",
                     "dc", "d", "a", "a", "bc", "ab"
                     )) +
  theme_classic()

plotly::ggplotly(Fig6)

DBH

Fig7 <- ggplot(hane_dbh,
               aes(x = Family, y = DBH, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 20), breaks = c(0, 5, 10, 15, 20), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "DBH: Family Effect") +
  xlab("Family") +
  ylab("DBH (cm)") +
  annotate("text",
           x = c(1, 2, 3, 4, 5, 6),
           y = c(15),
           label = c("d", "cd", "b", "b", "cb", "a")) +
  theme_classic()

plotly::ggplotly(Fig7)

Fig8 <- ggplot(hane_dbh,
               aes(x = Year, y = DBH, fill = Location)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 20), breaks = c(0, 5, 10, 15, 20), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#000000", "#999999"), 0.5)) +
  labs(title = "DBH: Year * Location" ) +
  xlab("Growing Season") +
  ylab("DBH (cm)") +
  annotate("text",
           x = c(0.78, 1.22, 1.78, 2.22, 2.78, 3.22, 3.78, 4.22, 4.78, 5.22),
           y = c(5, 4, 8, 7, 11, 10, 13, 12, 14, 13),
           label = c("a", "b", "a", "b", "a", "b", "a", "b", "a", "b")) +
  theme_classic()

plotly::ggplotly(Fig8)

Fig9 <- ggplot(hane_dbh,
               aes(x = Year, y = DBH, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 20), breaks = c(0, 5, 10, 15, 20), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "DBH: Year * Family") +
  xlab("Growing Season") +
  ylab("DBH (cm)") +
  annotate("text",
           x = c(0.63, 0.77, 0.92, 1.06, 1.22, 1.38,
                 1.63, 1.77, 1.92, 2.06, 2.22, 2.38,
                 2.63, 2.77, 2.92, 3.06, 3.22, 3.38,
                 3.63, 3.77, 3.92, 4.06, 4.22, 4.38,
                 4.63, 4.77, 4.92, 5.06, 5.22, 5.38
           ),
           y = c(3.2, 3.5, 5, 5.3, 4.7, 4.9,
                 6.1, 6.3, 7.8, 7.9, 7.5, 8.5,
                 8.9, 9.3, 10.1, 10.2, 10.8, 11.8,
                 11.1, 11.3, 11.9, 12.3, 12.8, 13.2,
                 12.7, 12.7, 12.9, 13.1, 13.5, 14.7
           ),
           label = c("c", "c", "ab", "a", "bc", "a",
                     "d", "cd", "b", "b", "bc", "a",
                     "c", "c", "b", "b", "b", "a",
                     "d", "cd", "bcd", "bc", "b", "a",
                     "b", "b", "b", "b", "b", "a"
           )) +
  theme_classic()

plotly::ggplotly(Fig9)

Crown

Fig10 <- ggplot(hane_crown,
                aes(x = Family, y = Crown, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 10), breaks = c(0, 2, 4, 6, 8, 10), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "Crown Height: Family Effect") +
  xlab("Family") +
  ylab("Crown Height (m)") +
  annotate("text",
           x = c(1, 2, 3, 4, 5, 6),
           y = c(8),
           label = c("b", "b", "a", "a", "a", "a")) +
  theme_classic()

plotly::ggplotly(Fig10)

Fig11 <- ggplot(hane_crown,
               aes(x = Year, y = Crown, fill = Location)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 10), breaks = c(0, 2, 4, 6, 8, 10), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#000000", "#999999"), 0.5)) +
  labs(title = "Crown Height: Year * Location" ) +
  xlab("Growing Season") +
  ylab("Crown Height (m)") +
  annotate("text",
           x = c(0.78, 1.22, 1.78, 2.22, 2.78, 3.22),
           y = c(3.2, 1.7, 6.5, 4, 7.3, 5),
           label = c("a", "b", "a", "b", "a", "b")) +
  theme_classic()

plotly::ggplotly(Fig11)

Fig12 <- ggplot(hane_crown,
               aes(x = Year, y = Crown, fill = Family)) +
  stat_summary(fun.data = mean_sd, geom = "errorbar", position = position_dodge(0.9), width = 0.2, color = "grey") +
  stat_summary(fun = mean, geom = "bar", position = "dodge") +
  font("title", size = 22) +
  font("xlab", size = 18) +
  font("ylab", size = 18) +
  font("xy.text", size = 16) +
  scale_y_continuous(limits = c(0, 10), breaks = c(0, 2, 4, 6, 8, 10), expand = c(0,0)) +
  scale_fill_manual(values = alpha(c("#E69F00", "#56B4E9", "#009E73",
                                     "#F0E442", "#D55E00", "#CC79A7"), 0.5)) +
  labs(title = "Crown Height: Year * Family") +
  xlab("Growing Season") +
  ylab("Crown Height (m)") +
  annotate("text",
           x = c(1.63, 1.77, 1.92, 2.06, 2.22, 2.36,
                 2.63, 2.77, 2.92, 3.06, 3.22, 3.36
           ),
           y = c(2.5, 3.4, 6, 6.5, 5.5, 5.7,
                 4, 3.9, 7.2, 7.3, 6.1, 6.6
           ),
           label = c("b", "b", "a", "a", "a", "a",
                     "b", "b", "a", "a", "a", "a"
           )) +
  theme_classic()

plotly::ggplotly(Fig12)